How data analysis gets less complicated

1. Apache Spark

This is supposed to be a convenient big data analytics tool which is able to assist in large SQL, streaming processes and so on. Apache Spark is rather similar to Apache Hadoop, which is an open source platform to process data. This is a valuable option for a more unified analytics method designed to serve both data understanding and big data.

In order to make the most out of this tool, users should operate in on Hadoop base to set up new apps being able to leverage the power, create more valuable insights as well as develop data science workloads in a single database.

There are some certain reasons proving why you should go for Apache Spark. First of all, it is a unified method, which is mainly made to generate and connect complicated workflows in terms of SQL queries, machine learning and advanced libraries. Moreover, this is an engine born for processing data. With Apache Spark, data specialists are able to execute machine learning in APIs development which is in need of quicker approach to data. Last but not least, APIs of this solution is very easy to utilize. To be more specific, it provides you with more than 100 operators to transform data for a more structured data source.

2. SAP Business Intelligence Platform

This is another tool used to control the major metrics as well as develop the value for insights in terms of customer behavior while reducing the complication in process. The major aim of this solution is to be a Business Intelligence solution for providing information which is useful. What is more, SAP is an ideal option as it is suitable for both cloud and on premises. There are a lot of different tools in this platform utilized to deal with every specific requirement and speed up the decision making process. There are some major points that make this platform worth utilizing. Data visualization is the first value. With the major purpose of making data less difficult to understand, this method assists users in a lot of skills to generate the smartest decisions. Finally, users are able to have approach to data at any time and any location.

3. Minitab

Minitab is another solution offering intelligent data analysis for entrepreneurs to advance their service quality while doing things more effectively. Its flagship product named Minitab Statistical Software is currently being taken advantage by entrepreneurs to make analysis for data. At this time, Minitab is considered to be an effective method offering valuable software for all entrepreneurs to help them seek for the most efficient solutions to their issues.

With such tools, users do not need to be so professional to learn and be clear about the data because the function Assistance of this tool will give you clear tutorials. There are other modules which are suitable for analyzing data as well as making reports and other analysis.

There are three major advantages of Minitab. First of all, this solution is very economical as you are offered e-learning tutorials to make the most out of this tool. It means you would know clearly how you should analyze your data on the Internet. Secondly, you would appreciate its project roadmaps. This function means that every process from executing and project sharing will be carried out effectively in your company. Last but not least, the assistant function is so valuable. Users can analyze data and predict the results with a high level of accuracy so that they would know how to advance their products.

4. Stata

Stata is the name of another data analytics software used to get, exploit and stimulate data value. With Stata, you are able to visualize and improve results in your reports. This tool is invented by researchers to meet the needs of professional software advancing. This tool is a complete package including data management, analysis and graphics. The most highlighted point of this tool is that it is quick, simple and safe. The results yielded are really effective no matter when scripts are written, which is expected among specialists. In terms of why you should go for Stata, there are three major reasons: managing data abilities, statistical methods and public graphics. To be more specific, users can control completely all data types. Stata also has the ability to control variables, optimize data as well as collect figures throughout different groups. Also, Stata will collect numerous features from standard methods to more improved ones such as conducting survey for data and modeling structure. Finally, thanks to Stata, users will be provided with opportunities to set up their own customized graph so that they can establish a graph with high quality and valuable style.

5. Rapid Miner

The last choice in this article is Rapid Miner, which is designed to be a data science base. This solution is mainly for analytic groups who need to make preparation for data, establishing predictive models as well as model deployment within a single system. Rapid Miner is really valuable as it will provide you with a good technology to deal with different issues such as analyzing a complicated project or working with numerous languages. What is more, these solutions are designed with machine learning, app integration, data transformation as well as integration. Rapid Miner is so effective in making the predictions by analyzing apart from its wonderful access in learning and understanding the important data processes. Finally, this solution is so supportive in terms of data science to meet the needs of businesses.

To sum up, we can look back why we should opt for Rapid Miner as it is better to be clear about what you are going to choose. Rapid Miner supports the demands of data science via its very large community of data science specialists and many open languages as well as technology. This open source platform is also able to collaborate with over 60 connectors for every kind of data ranging from structured to unstructured one.